Matthieu Terris
Github · Google Scholar · Linkedin

I am currently a postdoctoral researcher within the MIND team at INRIA, focusing on machine learning techniques inverse problems and image restoration. I obtained my PhD from the Biomedical and Astronomical Signal Processing (BASP) laboratory at Heriot-Watt University, Edinburgh, UK under the supervision of Prof. Yves Wiaux and Prof. Jean-Christophe Pesquet. Feel free to reach me by email :)

Contact: matthieu.terris@gmail.com

Software

DeepInverse A torch-based library for solving inverse problems, joint work with Dongdong, Samuel and Julian. Check it out!
[github] [doc]

Preprints

2023 Equivariant plug-and-play image reconstruction, Matthieu Terris*, Thomas Moreau, Nelly Pustelnik, Julian Tachella
arxiv
[PDF]
2023 Meta-Prior: Meta learning for Adaptive Inverse Problem Solvers, Matthieu Terris*, Thomas Moreau
arxiv
[PDF]
2023 Plug-and-play imaging with model uncertainty quantification in radio astronomy, Matthieu Terris*, Chao Tang*, Adrian Jackson, Yves Wiaux
arxiv
[PDF]

Published or Accepted Journal Articles

2023 Scalable precision wide-field imaging in radio interferometry–II. AIRI validated on ASKAP data, Amanda Wilber*, Arwa Dabbech, Matthieu Terris, Adrian Jackson, Yves Wiaux
Monthly Notices of the Royal Astronomy Society, 2023
[PDF]
2022 First AI for deep super-resolution wide-field imaging in radio astronomy: unveiling structure in ESO 137-006, Arwa Dabbech*, Matthieu Terris, Adrian Jackson, Mpati Ramatsoku, Oleg M Smirnov, Yves Wiaux
The Astrophysical Journal Letters, 2023
[PDF]
2022 Image reconstruction algorithms in radio interferometry: from handcrafted to learned regularization denoisers, Matthieu Terris*, Arwa Dabbech, Chao Tang, Yves Wiaux
Monthly Notices of the Royal Astronomical Society, 2022
[PDF] [Code (coming soon)]
2021 Learning Maximally Monotone Operators for Image Recovery, Jean-Christophe Pesquet, Audrey Repetti*, Matthieu Terris*, Yves Wiaux
SIAM Journal on Imaging Sciences, 2021
[PDF] [Code]
2020 Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients, Nathalie Lassau, Samy Ammari, Emilie Chouzenoux, ..., Matthieu Terris, ..., et al
Nature Communications, 2021
[PDF] [Code]

Conference Proceedings

2023 Investigating Model Robustness Against Sensor Variation, Matthieu Terris*, Sagar Verma
IGARSS 2023.
[PDF]
2023 Have Foundational Models Seen Satellite Images?, PanigrahiMatthieu Terris*, Sagar Verma
IGARSS 2023.
[PDF]
2022 Deep network series for large-scale high-dynamic range imaging, Amir Aghabiglou*, Matthieu Terris*, Adrian Jackson, Yves Wiaux
ICASSP 2023.
[PDF]
2022 Dual Forward-Backward Unfolded Network for Flexible Plug-and-Play, Audrey Repetti*, Matthieu Terris, Jean-Christophe Pesquet, Yves Wiaux
EUSIPCO 2022.
[PDF] [Code (coming soon!)]
2021 Enhanced Convergent PnP Algorithms For Image Restoration, Matthieu Terris*, Audrey Repetti, Jean-Christophe Pesquet, Yves Wiaux
ICIP 2021
[PDF]
2020 Building Firmly Nonexpansive Convolutional Neural Networks, Matthieu Terris*, Audrey Repetti, Jean-Christophe Pesquet, Yves Wiaux
ICASSP 2020
[PDF]
2019 Deep Post Processing for Sparse Image Deconvolution, Matthieu Terris*, Abdullah Abdulaziz, Arwa Dabbech, Ming Jiang, Audrey Repetti, Jean-Christophe Pesquet, Yves Wiaux
SPARS 2019
[PDF]
2019 Stochastic MM Subspace Algorithms, Matthieu Terris, Emilie Chouzenoux
BASP 2019
[PDF]

* denotes equal contribution/corresponding author.

PhD Thesis

2022 Learning priors for scalable computational imaging algorithms, from theory to application in radio astronomy
Heriot-Watt University, 2022.
[PDF]